AI ML Expert

Key Responsibilities:

• Gather, clean, and preprocess structured and unstructured data for analysis.
• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights.
• Develop, train, and validate machine learning models to address business challenges.
• Implement deep learning algorithms where applicable for advanced analytics.
• Create interactive dashboards and reports to visualize insights using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn, Plotly).
• Communicate results and recommendations effectively to stakeholders.
• Integrate ML models into production environments and ensure their scalability and performance.
• Use tools like TensorFlow Serving, Flask, FastAPI, or Docker for model deployment.
• Work closely with cross-functional teams, including data engineers, business analysts, and product planning team, to understand project requirements.
• Stay updated with the latest trends, technologies, and methodologies in data science, machine learning, and AI.
• Optimize existing models and systems for improved performance and accuracy.

Requirements:

• Minimum 1 (BE) to 6 years relevant job experience.
• B.E in AI or CS or E&C or EEE or Mechatronics.
• Certifications in AI/ML or data analytics (e.g., Google Data Analytics, TensorFlow Developer, AWS Certified Machine Learning).
• Experience with natural language processing (NLP), computer vision, or reinforcement learning.

Required Skills and Qualifications:

• Educational Background: Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
• Technical Skills: Proficiency in Python, R, or Julia.
• Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong knowledge of SQL and NoSQL databases.
• Familiarity with big data tools like Spark, Hadoop, or Databricks is a plus.
• Knowledge of cloud platforms like AWS, Azure, or Google Cloud for data and model deployment.
• Analytical Skills: Strong understanding of statistics, probability, and data structures.
• Ability to handle large datasets and apply algorithms efficiently.
• Soft Skills: Excellent problem-solving and critical-thinking skills.
• Strong communication and teamwork capabilities.
• Ability to translate business requirements into technical solutions.